A variety of commercially available implantable medical devices (IMDs) are available, which collect physiological signals from sensors and extract and store data from those signals. These IMDs are often capable of delivering therapies and storing data relating to the success of those therapies. Examples of such IMDs include pacemakers, implantable cardioverter defibrillators (ICDs), cardiac monitors, neurostimulators, and drug pumps.
Expanding clinical databases receive IMD data from patients through networked remote patient monitoring systems. An ever-growing amount of data pertaining to individual patients and patient populations is stored in these databases. Clinicians strive to make the best treatment decisions possible for an individual patient. Yet many programmable parameters exist in a given IMD, sometimes more than one hundred programmable parameter settings may be available. Determining optimal operating parameters of a programmable IMD can be a time-consuming task. Selecting optimal IMD operating parameters is among many other treatment options a clinician may have, including prescription medications and surgical interventions. Since knowledge and understanding of medical conditions and the mechanisms of benefit of relevant therapies is always evolving, the best medical practices for treating a patient may be dynamic and difficult to ascertain from an individual patient or small group of patients.
Current medical database systems make individual patient data available to authorized users. The vast amount of data stored in medical databases, however, may be an under-used source of valuable information that could help clinicians develop and improve best practices for treating a wide variety of patients.